Lists all tables in one or more schemas. By default returns a compact summary. Set verbose to true to include column details, primary keys, and foreign key constraints.
Bulk support: accepts project_ids for batched execution.
| Name | Required | Description | Default |
|---|---|---|---|
| schemas | Yes | ||
| verbose | Yes | ||
| project_id | Yes | ||
| project_ids | No |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Given annotations already declare readOnlyHint and idempotentHint, the description adds value by specifying output behavior (compact summary vs. verbose) and bulk capability. It does not cover authentication or rate limits, but for a read/list operation with these annotations, the spirit of the description aligns and adds meaningful context beyond the structured fields.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is elegantly brief: two sentences. The first states the purpose and default behavior; the second covers optional parameters and bulk support. Minimal redundant text, front-loads the core action, and stays focused to essential information without bloat.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool has no output schema and only annotations; the description covers the main behaviors (default/verbose, bulk) and gives enough context to understand operation. It lacks a note on return format (e.g., whether it's a paginated list) and error scenarios, but for a list operation it is nearly complete. The absence of an output schema makes it slightly less complete than the high-calibration example.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description's job is important. It clarifies verbose toggling behavior, schemas scope, and project_ids for batching. It does not expand on project_id, but its purpose is obvious from the name and required status. Overall, it compensates for the absent schema descriptions with clear, actionable parameter semantics.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool lists tables across schemas, with a specific verb-resource pair and scope. It distinguishes itself from sibling list tools (e.g., supabase_list_projects, supabase_list_branches) by targeting tables in schemas. Confusion with siblings is unlikely.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides usage context: by default a compact summary is returned, verbose includes column details, and a bulk mode uses project_ids for batching. It implies when to choose verbose (need detail) and when to use bulk (multiple projects), but it does not explicitly name alternatives or say when not to use this tool. Slight improvement would be an explicit exclusions line.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
The Supabase-prefixed tools are all distinct CRUD/lifecycle operations on different resource types (projects, branches, migrations, edge functions, etc.). The platform-level tools (authenticate, connect, marketplace, etc.) have clear non-overlapping purposes, though their names could momentarily be confused with Supabase-specific actions if an agent doesn't read descriptions.
The 29 supabase_* tools follow a consistent 'supabase_<verb>_<noun>' pattern. However, the 6 non-prefixed platform tools (authenticate, connect, marketplace, report_bug, show_version, toolkit_info) break this convention and are inconsistent among themselves, creating a mixed naming style across the set.
At 35 tools, the server is overweight. While the Supabase domain is broad (project management, database, edge functions, branches), the inclusion of 6 unrelated platform tools inflates the count. 29 domain tools still exceeds the comfortable 15-tool upper bound, making the surface feel bloated for agents to navigate.
The tool set covers core workflows: project lifecycle (create, get, list, pause, restore), branching (create, delete, list, merge, rebase, reset), SQL/migrations, edge functions, cost estimation, and advisors. However, there are notable gaps such as no delete_project, no update operations for projects or branches, and no deletion for edge functions, which leave lifecycle coverage incomplete.